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https://github.com/bradyfu/dvg-face
[TPAMI 2021] DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition
https://github.com/bradyfu/dvg-face
face-recognition heterogeneous-face-recognition pytorch
Last synced: 8 days ago
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[TPAMI 2021] DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition
- Host: GitHub
- URL: https://github.com/bradyfu/dvg-face
- Owner: BradyFU
- License: mit
- Created: 2020-09-20T08:50:33.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2023-11-13T03:11:55.000Z (about 1 year ago)
- Last Synced: 2023-11-13T04:24:11.111Z (about 1 year ago)
- Topics: face-recognition, heterogeneous-face-recognition, pytorch
- Language: Python
- Homepage:
- Size: 1.19 MB
- Stars: 68
- Watchers: 5
- Forks: 16
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# DVG-Face: Dual Variational Generation for HFR
This repo is a [PyTorch](https://pytorch.org/) implementation of [DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition](https://arxiv.org/pdf/2009.09399.pdf), which is an extension version of our previous [conference paper](https://github.com/BradyFU/DVG). Compared with the previous one, this version has more powerful performances.
## Our Heterogeneous Face Recognition Works
✨ [**DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition**](https://arxiv.org/pdf/2009.09399.pdf)
- Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. **IEEE TPAMI 2021**
✨ [**Dual Variational Generation for Low Shot Heterogeneous Face Recognition**](https://proceedings.neurips.cc/paper/2019/file/b5a1fc2085986034e448d2ccc5bb9703-Paper.pdf)
- Chaoyou Fu, Xiang Wu, Yibo Hu, Huaibo Huang, and Ran He. **NeurIPS 2019**
✨ [**Towards Lightweight Pixel-Wise Hallucination for Heterogeneous Face Recognition**](https://ieeexplore.ieee.org/abstract/document/9971748)
- Chaoyou Fu, Xiaoqiang Zhou, Weizan He, and Ran He. **IEEE TPAMI 2022**
✨ [**Cross-Spectral Face Hallucination via Disentangling Independent Factors**](https://openaccess.thecvf.com/content_CVPR_2020/papers/Duan_Cross-Spectral_Face_Hallucination_via_Disentangling_Independent_Factors_CVPR_2020_paper.pdf)
- Boyan Duan, Chaoyou Fu, Yi Li, Xingguang Song, and Ran He. **CVPR 2020**
## Prerequisites
- Python 3.7.0 & PyTorch 1.5.0 & Torchvision 0.6.0
- Download LightCNN-29 [[Google Drive](https://drive.google.com/file/d/1Jn6aXtQ84WY-7J3Tpr2_j6sX0ch9yucS/view)] pretrained on MS-Celeb-1M.
- Download Identity Sampler [[Google Drive](https://drive.google.com/file/d/1kezDpwqA4a3WGq5PfS1kDrASf3-bN4js/view?usp=sharing)] pretrained on MS-Celeb-1M.
- Put the above two models in `./pre_train`
## Train the generator
`train_generator.py`:
Fill out options of '--img_root' and '--train_list', which are the image root and training list of the heterogeneous data, respectively.
An example of the training list:
```
NIR/s2_NIR_10039_001.jpg 232
VIS/s1_VIS_00134_010.jpg 133
NIR/s1_NIR_00118_011.jpg 117
```
Here we use 'NIR' and 'VIS' in the training list to distinguish the modalities of images. If your list has other distinguishable marks,
please change them correspondingly in `./data/dataset.py` (lines 28, 38, 66, and 68).
```
python train_generator.py --gpu_ids 0
```
## Generate images from noise
`gen_samples.py`:
Fill out options of '--img_root' and '--train_list' that are the same as the above options.
```
python gen_samples.py --gpu_ids 0
```
The generated images will be saved in `./gen_images`
## Train the recognition model LightCNN-29
`train_lightcnn.py`:
Fill out options of 'num_classes', '--img_root_A', and '--train_list_A', where the last two options are the same as the above options.
```
python train_ligthcnn.py --gpu_ids 0,1
```
## Citation
If you use our code for your research, please cite the following papers:
```
@article{fu2021dvg,
title={DVG-face: Dual variational generation for heterogeneous face recognition},
author={Fu, Chaoyou and Wu, Xiang and Hu, Yibo and Huang, Huaibo and He, Ran},
journal={IEEE TPAMI},
year={2021}
}
@inproceedings{fu2019dual,
title={Dual Variational Generation for Low-Shot Heterogeneous Face Recognition},
author={Fu, Chaoyou and Wu, Xiang and Hu, Yibo and Huang, Huaibo and He, Ran},
booktitle={NeurIPS},
year={2019}
}
@article{fu2022towards,
title={Towards Lightweight Pixel-Wise Hallucination for Heterogeneous Face Recognition},
author={Fu, Chaoyou and Zhou, Xiaoqiang and He, Weizan and He, Ran},
journal={IEEE TPAMI},
year={2022}
}
@inproceedings{duan2020cross,
title={Cross-spectral face hallucination via disentangling independent factors},
author={Duan, Boyan and Fu, Chaoyou and Li, Yi and Song, Xingguang and He, Ran},
booktitle={CVPR},
year={2020}
}
```